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|Title:||Development and applications of a sequential, minimal, radial basis function (RBF) neural network learning algorithm||Authors:||Lu, Ying Wei.||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems||Issue Date:||1997||Abstract:||This thesis presents a new sequential learning algorithm for realizing a minimal Radial Basis Function (RBF) neural network, referred to as M-RAN (Minimal Resource Allocation Network). Unlike most of the classical RBF neural networks with the number of hidden neurons fixed apriori, the network structure is dynamic in the proposed M-RAN algorithm.||URI:||http://hdl.handle.net/10356/39014||Rights:||NANYANG TECHNOLOGICAL UNIVERSITY||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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